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WebSearchAgent Documentation

WebSearchAgent is a powerful tool for conducting internet-based research on any topic. It leverages language models and web search capabilities to gather, process, and summarize information from online sources.

Basic Usage

from ursa.agents import WebSearchAgent
from langchain_openai import ChatOpenAI

# Initialize with default model (gpt-5-mini)
websearcher = WebSearchAgent()

# Or initialize with a custom model
model = ChatOpenAI(model="gpt-5-mini", max_completion_tokens=10000)
websearcher = WebSearchAgent(llm=model)

# Run a web search query
result = websearcher.invoke("Who are the 2025 Detroit Tigers top 10 prospects and what year were they born?")

# Access the web search results
final_summary = result["messages"][-1].content
sources = result["urls_visited"]

print("Web Search Summary:")
print(final_summary)
print("Sources:", sources)

Parameters

Initialization

Parameter Type Default Description
llm BaseChatModel init_chat_model("openai:gpt-5-mini") The language model to use for web search
**kwargs dict {} Additional parameters passed to the base agent

Run Method

Parameter Type Default Description
prompt str Required The web search question or topic
recursion_limit int 100 Maximum recursion depth for the web search process

Features

  • Automated Web Search: Uses DuckDuckGo to find relevant information
  • Content Processing: Extracts and summarizes content from web pages
  • Iterative Web Search: Continues researching until sufficient information is gathered
  • Source Tracking: Records all URLs visited during research
  • Internet Connectivity Check: Verifies internet access before attempting research

Output

The agent returns a dictionary containing:

  • messages: A list of message objects, with the final message containing the comprehensive web search summary
  • urls_visited: A list of all sources consulted during the web search process

Advanced Usage

from langchain.chat_model import init_chat_model
from ursa.agents import WebSearchAgent

# Initialize with custom parameters
websearcher = WebSearchAgent(
    llm=init_chat_model("openai:gpt-5-mini"),
    url="https://www.example.com"  # Custom URL for internet connectivity check
)

# Run with higher recursion limit for complex topics
result = websearcher.invoke(
    "What are the latest developments in quantum computing? Summarize in markdown format.",
    recursion_limit=200
)

Notes

  • The agent requires internet connectivity to function properly
  • Rate limiting is implemented to avoid overwhelming search services
  • For networks with SSL inspection, you may need to set the CERT_FILE environment variable
  • The websearch process includes multiple steps: search, content processing, review, and final summarization